Prognostic evaluation and immune infiltration analysis of five bioinformatic selected genes in hepatocellular carcinoma.
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ABSTRACT:
SUBMITTER: Lai E
PROVIDER: S-EPMC8650024 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Hepatocellular carcinoma (HCC) has a high degree of malignancy and a poor prognosis. Immune infiltration-related genes have shown good predictive value in the prognosis of many solid tumours. In this study, we established and verified prognostic biomarkers consisting of immune infiltration-related genes in HCC. Gene expression data and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Differential gene expression analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression algorithm were used to screen prognostic immune infiltration-related genes and to construct a risk scoring model. Kaplan-Meier (KM) survival plots and receiver operating characteristic (ROC) curve analysis were used to evaluate the prognostic performance of the risk scoring model in the TCGA-HCC cohort. In addition, a nomogram model with a risk score was established, and its predictive performance was verified by ROC analysis and calibration plot analysis in the TCGA-HCC cohort. Gene set enrichment analysis (GSEA) identified pathways and biological processes that may be enriched in the high-risk group. Finally, immune infiltration analysis was used to explore the characteristics of the tumour microenvironment related to the risk score. We identified 17 immune infiltration-related genes with prognostic value and constructed a risk scoring model. ROC analysis showed that the risk scoring model can accurately predict the 1-year, 3-year, and 5-year overall survival (OS) of HCC patients in the TCGA-HCC cohort. KM analysis showed that the OS of the high-risk group was significantly lower than that of the low-risk group (P < 0.001). The nomogram model effectively predicted the OS of HCC patients in the TCGA-HCC cohort. GSEA indicated that the immune infiltration-related genes may be involved in biological processes such as amino acid and lipid metabolism, matrisome and small molecule transportation, immune system regulation, and hepatitis virus infection. Immune infiltration analysis showed that the level of immune cell infiltration in the high-risk group was low, and the risk score was negatively correlated with infiltrating immune cells. Our prognostic model based on immune infiltration-related genes in HCC could help the prognostic assessment of HCC patients and provide potential targets for HCC inhibition.
| S-EPMC9074323 | biostudies-literature
Project description:Background: Increasing evidence supports that competing endogenous RNAs (ceRNAs) and tumor immune infiltration act as pivotal players in tumor progression of hepatocellular carcinoma (HCC). Nonetheless, comprehensive analysis focusing on ceRNAs and immune infiltration in HCC is lacking. Methods: RNA and miRNA sequencing information, corresponding clinical annotation, and mutation data of HCC downloaded from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) project were employed to identify significant differentially expressed mRNAs (DEMs), miRNAs (DEMis), and lncRNAs (DELs) to establish a ceRNA regulatory network. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene ontology (GO) enrichment pathways were analyzed to functionally annotate these DEMs. A multigene-based risk signature was developed utilizing least absolute shrinkage and selection operator method (LASSO) algorithm. Moreover, survival analysis and receiver operating characteristic (ROC) analysis were applied for prognostic value validation. Seven algorithms (TIMER, XCELL, MCPcounter, QUANTISEQ, CIBERSORT, EPIC, and CIBERSORT-ABS) were utilized to characterize tumor immune microenvironment (TIME). Finally, the mutation data were analyzed by employing "maftools" package. Results: In total, 136 DELs, 128 DEMis, and 2,028 DEMs were recognized in HCC. A specific lncRNA-miRNA-mRNA network consisting of 3 lncRNAs, 12 miRNAs, and 21 mRNAs was established. A ceRNA-based prognostic signature was established to classify samples into two risk subgroups, which presented excellent prognostic performance. In additional, prognostic risk-clinical nomogram was delineated to assess risk of individual sample quantitatively. Besides, risk score was significantly associated with contexture of TIME and immunotherapeutic targets. Finally, potential interaction between risk score with tumor mutation burden (TMB) was revealed. Conclusion: In this work, comprehensive analyses of ceRNAs coexpression network will facilitate prognostic prediction, delineate complexity of TIME, and contribute insight into precision therapy for HCC.
| S-EPMC8473911 | biostudies-literature
Project description:Background: BTBD10 serves as an activator of Akt family members through decreasing the protein phosphatase 2A-mediated dephosphorylation. The present study attempted to investigate the prognostic value of BTBD10 in hepatocellular carcinoma (HCC), specially, its relationship with tumor-infiltrating lymphocytes (TILs). Methods: BTBD10 expression was evaluated in HCC using The Cancer Genome Atlas (TCGA) and Xijing Hospital database, and verified in HCC cell lines. Cox analyses were performed to analyze independent prognostic risk factors for HCC. The optimal cut-off value of BTBD10 was calculated, by which all patients were divided into two groups to compare the overall survival (OS). The signaling pathways were predicted, by which BTBD10 may affect the progression of HCC. To investigate the impact of BTBD10 on HCC immunotherapy, correlations between BTBD10 and TILs, immune checkpoints, m6A methylation-related genes and ferroptosis-related genes were assessed. The distribution of half-maximal inhibitory concentration (IC50) of diverse targeted drugs was observed based on the differential expression of BTBD10. Results: BTBD10 expression was higher in HCC tissues and cell lines than that of normal liver tissues and cells. The patients with high expression of BTBD10 showed a worse OS, as compared to that of BTBD10 low-expressing group. Cox analyses indicated that BTBD10 was an independent prognostic risk factor for HCC. Several molecular pathways of immune responses were activated in HCC patients with high-expressing of BTBD10. Furthermore, BTBD10 expression was demonstrated to be positively correlated with tumor-infiltrating B cells, T cells, macrophages, neutrophils and dendritic cells. Meanwhile, the expression of BTBD10 was synchronized with that of several m6A methylation-related genes, ferroptosis-related genes and immune checkpoints. The IC50 scores of Sorafenib, Navitoclax, Veliparib, Luminespib, and Imatinib were found to be lower in BTBD10 high-expressing HCC group. Conclusion: BTBD10 negatively regulates tumor immunity in HCC and exhibits adverse effect on the prognosis of HCC, which could be a potential target for immunotherapy.
| S-EPMC8764259 | biostudies-literature
Project description:The poliovirus receptor (PVR) is a member of the immunoglobulin superfamily (Ig SF) and is essential for the promotion of cancer cell proliferation and invasion. However, the correlation between PVR expression and prognosis as well as immune infiltration in hepatocellular carcinoma (HCC) remains unclear. The expression level of PVR was quantified using the Tumor and Tumor Immunity Evaluation Resource (TIMER) and Sangerbox. The Gene Expression Omnibus (GEO) database was used to validate the PVR expression. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of using PVR as a differentiating factor according to the area under curve (AUC) score. A PVR binding protein network was built using the STRING tool. An enrichment analysis using the R package clusterProfiler was used to explore the potential function of PVR. Immune infiltration analysis was calculated with ESTIMATE algorithms. We also assessed the correlation between PVR expression and immune infiltration by the single-sample Gene Set Enrichment Analysis (ssGSEA) method from the R package GSVA and TIMER database. The results showed that PVR was commonly overexpressed in multiple types of tumors including HCC. The data of GSE64041 confirmed the same result. The ROC curve suggested that PVR could be a potential diagnostic biomarker. Additionally, high mRNA expression of PVR in HCC was significantly correlated with poor overall survival (OS) and relapse free survival (RFS). Results also indicated correlations between PVR mRNA expression with the level of infiltration immune cells including B cells, CD8+ T cells, cytotoxic cells, DCs, CD56dim NK cells, pDCs, and Th2 cells. Furthermore, the PVR level was significantly correlated with immune markers for immunosuppressive cells in HCC. In conclusion, PVR might be an important regulator of tumor immune cell infiltration and a valuable prognostic biomarker in HCC. However, additional work is needed to fully elucidate the underlying mechanisms.
| S-EPMC9777148 | biostudies-literature
Project description:Background: Previous studies have shown that Leukocyte cell-derived chemotaxin2 (LECT2) is associated with the development of HCC. However, there are still no studies with a comprehensive analysis of the role of LECT2 in hepatocellular carcinoma (HCC). Methods: TCGA data sets were used to analyze the expression of LECT2 in HCC. In addition, the prognostic value of LECT2 in HCC was also investigated. DriverDBv3 was used to analyze the Mutation, CNV, and methylation profiles of LECT2. And, validated by immunohistochemistry in 72 HCC samples. The prognostic value of LECT2 and the correlation with clinicopathological features were analyzed. The GO/KEGG enrichment analysis of LECT2 co-expression and gene set enrichment analysis (GSEA) was performed using the R software package. The PPI interaction network was constructed by Search Tool for the Retrieval of Interacting Genes (STRING) database. Immune infiltration was estimated by the XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, CIBERSORT abs and CIBERSORT algorithms, and Spearman was used to analyzing their correlation with LECT2. Moreover, we analyzed the correlation of LECT2 expression with immune checkpoint molecules and HLA genes. Finally, we analyzed the IC50 values of six chemotherapeutic drugs by the pRRophetic package. Results: Reduced LECT2 expression levels found in HCC patients. Moreover, decreased levels of LECT2 were associated with poor overall survival, disease-free survival, disease-specific survival, and progression-free survival. Besides, methylation was significantly associated with LECT2 expression. The functional enrichment analysis revealed that LECT2 may affect HCC progression through various pathways such as JAK/STAT signaling pathway, cell cycle, and pathways in cancer. Additionally, the results showed that LECT2 expression was negatively correlated with immune infiltration of B cells, Neutrophil, Monocyte, Cancer-associated fibroblast, and Myeloid dendritic cell, and positively correlated with T cell CD8+ naive, Endothelial cell, and Hematopoietic stem cell. LECT2 expression was negatively correlated with multiple immune checkpoint molecules and HLA genes. Chemosensitivity analysis showed that chemosensitivity was lower in the LECT2 high expression group. We validated the prognostic value of LECT2 and analysis of clinicopathological features showed a lower TNM stage in the group with high expression of LECT2. Conclusion: Low expression of LECT2 in HCC is closely associated with poor prognosis, LECT2 may have potential clinical applications due to its unique immunological effects.
| S-EPMC9500357 | biostudies-literature
Project description:BackgroundA preliminary study by our group revealed that the deficiency of EGF domain-specific O-linked N-acetylglucosamine transferase (EOGT) impaired regulatory T-cell differentiation in autoimmune hepatitis. Nevertheless, the prognostic value of EOGT in advanced hepatocellular carcinoma (HCC) and its relationship with immune infiltration remain obscured.MethodsInitially, EOGT expression was evaluated by Oncomine, TIMER, GEO, and UALCAN databases. Besides, the prognostic potential of EOGT expression was analyzed using GEPIA, Kaplan-Meier plotter, CPTAC, Cox regression, and nomogram in HCC samples. Furthermore, we investigated the association between EOGT expression and tumor mutation burden, DNA methylation, and immune infiltration in addition to its possible mechanism via cBioPortal, TIMER, GEPIA, ESTIMATE, CIBERSORT, GSEA, STRING, and Cytoscape.ResultsThe expression of EOGT in HCC was significantly higher than that in normal tissues. Additionally, elevated EOGT expression was correlated with advanced tumor staging and linked to poor overall survival and relapse-free survival, serving as a significant unfavorable prognostic indicator in HCC patients. Remarkably, our results revealed that high-EOGT expression subgroups with elevated TP53 or low CTNNB1 mutations have worse clinical outcomes than the others. Regarding immune infiltration, immunofluorescent staining showed that immune cells in HCC were positive for EOGT. Besides, elevated EOGT expression was linked to exhausted T cells and immune suppressor cells in HCC samples. More importantly, the proportion of CD8+ T cells was reduced in HCC samples with a high level of EOGT expression, but EOGT did not exhibit prognostic potential in HCC samples with increased CD8+ T cells.ConclusionsEOGT may hold great potential as a novel biomarker to distinguish prognosis and immune profiles of HCC patients.
| S-EPMC8766744 | biostudies-literature
Project description:BackgroundThe dysregulated PI3K/AKT/mTOR pathway acts as the main regulator of tumorigenesis in hepatocellular carcinoma (HCC).AimHere, we identify the prognostic significance of PI3K/AKT/mTOR pathway-associated genes (PAGs) as well as their putative signature based on PAGs in an HCC patient's cohort.MethodsThe transcriptomic data and clinical feature sets were queried to extract the putative prognostic signature.ResultsWe identified nine PAGs with different expressions. GO and KEGG indicated that these differentially expressed genes were associated with various carcinogenic pathways. Based on the signature-computed median risk score, we categorized the patients into groups of low risk and high risk. The survival time for the low-risk group is longer than that of the high-risk group in Kaplan-Meier (KM) curves. The prognostic value of risk score (ROC = 0.736) of receiver operating characteristic (ROC) curves performed better in comparison to that of other clinicopathological features. In both the GEO database and ICGC database, these outcomes were verified. The predictions of the overall survival rates in HCC patients of 1 year, 3 years, and 5 years can be obtained separately from the nomogram. The risk score was associated with the immune infiltrations of CD8 T cells, activated CD4 memory T cells, and follicular helper T cells, and the expression of immune checkpoints (PD-1, TIGIT, TIM-3, BTLA, LAG-3, and CTLA4) was positively relevant to the risk score. The sensitivity to several chemotherapeutic drugs can also be revealed by the signature. CDK1, PITX2, PRKAA2, and SFN were all upregulated in the tumor tissue of clinical samples.ConclusionA putative and differential dataset-validated prognostic signature on the basis of integrated bioinformatic analysis was established in our study, providing the immunotherapeutic targets as well as the personalized treatment in HCC with neoteric insight.
| S-EPMC9112180 | biostudies-literature
Project description:Cell division cycle-associated protein-3 (CDCA3) contributes to the regulation of the cell cycle. CDCA3 plays an important role in the carcinogenesis of various cancers; however, the association between CDCA3 expression, prognosis of patients, and immune infiltration in the tumor microenvironment is still unknown. Here, we demonstrated that CDCA3 was differentially expressed between the tumor tissues and corresponding normal tissues using in silico analysis in the ONCOMINE and Tumor Immune Estimation Resource (TIMER) databases. We analyzed the relationship between the expression of CDCA3 and prognosis of patients with hepatocellular carcinoma (HCC) using the Kaplan-Meier plotter database and Gene Expression Profiling Interactive Analysis (GEPIA). Furthermore, we determined the prognostic value of CDCA3 expression using univariate and multivariate analyses. We observed that CDCA3 expression closely correlated with immune infiltration and gene markers of infiltrating immune cells in the TIMER database. CDCA3 was highly expressed in the tumor tissues than in the adjacent normal tissues in various cancers, including HCC. Increased expression of CDCA3 was accompanied by poorer overall survival (OS), relapse-free survival (RFS), progression-free survival (PFS), and disease-specific survival (DSS). The correlation between CDCA3 expression and OS and disease-free survival (DFS) was also studied using GEPIA. CDCA3 expression was associated with the levels of immune cell infiltration and was positively correlated with tumor purity. Moreover, CDCA3 expression was associated with gene markers such as PD-1, CTLA4, LAG3, and TIM-3 from exhausted T cells, CD3D, CD3E, and CD2 from T cells, and TGFB1 and CCR8 located on the surface of Tregs. Thus, we demonstrated that CDCA3 may be a potential target and biomarker for the management and diagnosis of HCC.
| S-EPMC7869413 | biostudies-literature
Project description:ObjectiveTo assess the diagnostic value and clinical significance of nucleoporin 107 (NUP107) in hepatocellular carcinoma (HCC), and explore the possible mechanisms.MethodsThe transcriptomic and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) and GEO databases. Tissue specimens were collected from HCC patients in the Guangxi area. According to the expression levels and prognostic characteristics of NUP107, ROC curves and nomogram models were constructed using the R package.ResultsNUP107 was highly expressed in 26 human cancers including HCC, and was associated with advanced HCC staging and worse prognosis. NUP107 showed satisfactory ability to predict the prognosis of HCC patients (AUC >0.8). Results of gene set enrichment analysis (GSEA) further showed that NUP107 was mainly associated with cell cycle-related pathways such as the cell cycle, DNA replication, G2M checkpoint, E2F target, and mitotic spindle. In addition, NUP107 was also associated with immune infiltration in HCC and showed significant positive correlation with immune checkpoints (PD-L1 and TIM-3).
| S-EPMC10225238 | biostudies-literature
Project description:Background: GINS2 has been reported to have prognostic value in several solid tumors other than hepatocellular carcinoma (HCC), and its influence on tumor immunity has not been investigated thus far. Methods: The transcriptome profiles were retrieved from two public databases, GEO and TCGA. The median GINS2 expression was considered as cutoff to define GINS2 high and GINS2 low groups and to obtain differentially expressed genes. These genes were then subjected to KEGG pathway and gene ontology (GO) analysis and to gene set enrichment analysis (GSEA). Survival analyses according to GINS2 level were performed utilizing Kaplan-Meier plotter. TIMER database was adopted to investigate associations between GINS2 level and infiltrating immunocytes, and the correlation between immunocyte-related gene expression and GINS2 level was evaluated via GEPIA database. A 236-patient validation cohort were applied to confirm the bioinformatic results of TCGA and TIMER database. Results: GINS2 is augmented in tumorous tissues of HCC patients compared with nontumor specimens, and GINS2-overexpressed patients have poorer overall survival (OS) and disease-specific survival (DSS) than those with low GINS2 expression in HCC (P = 0.009 and P = 0.002 respectively). Cell cycle and DNA replication were two main processes that enriched in tumor cells overexpressed GINS2 gene (NES = 1.848, P = 0.007; and NES = 1.907, P = 0.005, respectively). Moreover, GINS2 correlates positively with markers of activated CD8+ and CD4+ T cells, as well as exhausted T lymphocytes. Conclusions: HCC patients overexpressed GINS2 have poorer prognoses than those with low GINS2 expression, possibly as a result of the function of GINS2 in cell cycle and DNA replication as well the exhaustion of T lymphocytes.
| S-EPMC8771526 | biostudies-literature